title: Comparison result of inversion of gravity data of a fault by particle swarm optimization and Levenberg-Marquardt methods.
abstract: The purpose of this study was to compare the performance of two methods for gravity inversion of a fault. First method [Particle swarm optimization (PSO)] is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. Second method [The Levenberg-Marquardt algorithm (LM)] is an approximation to the Newton method used also for training ANNs. In this paper first we discussed the gravity field of a fault, then describes the algorithms of PSO and LM And presents application of Levenberg-Marquardt algorithm, and a particle swarm algorithm in solving inverse problem of a fault. Most importantly the parameters for the algorithms are given for the individual tests. Inverse solution reveals that fault model parameters are agree quite well with the known results. A more agreement has been found between the predicted model anomaly and the observed gravity anomaly in PSO method rather than LM method.
authors.affiliation: Department of Computer, Faculty of engineering, Kangavar Branch, Islamic Azad University, Kangavar, Iran.
authors.forename: Reza
authors.initials: R
authors.lastname: Toushmalani
keywords: Fault; Gravity data; Inversion; Levenberg-Marquardt method; Particle swarm optimization